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Get Free AccessGlobal crop productivity faces a significant threat from climate change-induced drought stress (DS), which is vital for sustainable agriculture and global food security. Uncovering DS adaptation and tolerance mechanisms in crops is necessary to alleviate climate challenges. Innovative plant breeding demands revolutionary approaches to develop stress-smart plants. Metabolomics, a promising field in plant breeding, offers a predictive tool to identify metabolic markers associated with plant performance under DS, enabling accelerated crop improvement. Central to DS adaptation is metabolomics-driven metabolic regulation, which is critical for maintaining cell osmotic potential in crops. Recent innovations allow rapid mapping of specific metabolites to their genetic pathways, providing a valuable resource for plant scientists. Metabolomics-driven molecular breeding, integrating techniques such as mQTL and mGWAS, enhances our ability to discover key genetic elements linked to stress-responsive metabolites. This integration offers a beneficial platform for plant scientists, yielding significant insights into the complex metabolic networks underlying DS tolerance. Therefore, this review discusses (1) insights into metabolic regulation for DS adaptation, (2) the multifaceted role of metabolites in DS tolerance and nutritional/yield trait improvement, (3) the potential of single-cell metabolomics and imaging, (4) metabolomics-driven molecular breeding, and (5) the application of metabolic and genetic engineering for DS-tolerant crops. We finally propose that the metabolomics-driven approach positions drought-smart crops as key contributors to future food production, supporting the vital goal of achieving “zero hunger”.
Ali Raza, Muhammad Anas, Savita Bhardwaj, Rakeeb Ahmad Mir, Sidra Charagh, Minhas Elahi, Xinyue Zhang, Reyazul Rouf Mir, Wolfram Weckwerth, Alisdair R. Fernie, Kadambot Siddique, Zhangli Hu, Rajeev K. Varshney (2025). Harnessing metabolomics for enhanced crop drought tolerance. , 13(2), DOI: https://doi.org/10.1016/j.cj.2025.01.001.
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Type
Article
Year
2025
Authors
13
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1016/j.cj.2025.01.001
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